Name
Abstract | ||
|---|---|---|
Humans are experts in understanding others' intention. This capacity is essential to interact and collaborate with others. Thus, providing a robot with this capacity is a key improvement for further developments in socially interactive robotics. This work exploits a mirroring scenario between aa caregiver and a robot to develop an intention inference capacity without providing a priori knowledge to the robot. A sensory-motor architecture is used to learn autonomously associations between the robot's internal states and its perception. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/DEVLRN.2014.6982971 | ICDL-EPIROB |
Keywords | Field | DocType |
human-robot interaction,inference mechanisms,learning (artificial intelligence),intention inference learning,caregiver interaction,humans,intention inference capacity,mirroring scenario,robot internal states,sensory-motor architecture,socially interactive robotics,computer architecture,grounding,pediatrics,feature extraction,visualization | Robot learning,Social robot,Inference,Computer science,Exploit,Artificial intelligence,Mirroring,Robot,Perception,Machine learning,Robotics | Conference |
Citations | PageRank | References |
1 | 0.44 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cohen, L. | 1 | 1 | 0.44 |
| Abbassi, W. | 2 | 1 | 0.44 |
| Mohamed Chetouani | 3 | 590 | 59.47 |
| Sofiane Boucenna | 4 | 138 | 11.16 |